arXiv subjects

Hsiao-Lan Chiang

Publications and source records attributed to Hsiao-Lan Chiang.

4 recordsLinked to original sources

arXiv2019

Machine-Learning Beam Tracking and Weight Optimization for mmWave Multi-UAV Links

Millimeter-wave (mmWave) hybrid analog-digital beamforming is a promising approach to satisfy the low-latency constraint in multiple unmanned aerial vehicles (UAVs) systems, which serve as network infrastructure for flexible deployment. However, in highly dynamic multi-UAV environments, analog beam tracking becomes a critical challenge. The overhead of additional pilot transmission at the price of spectral efficiency is shown necessary to achieve high resilience in operation. An efficient method to deal with high dynamics of UAVs applies machine learning, particularly Q-learning, to analog beam tracking. The proposed Q-learning-based beam tracking scheme uses current/past observations to design rewards from environments to facilitate prediction, which significantly increases the efficiency of data transmission and beam switching. Given the selected analog beams, the goal of digital beamforming is to maximize the SINR. The received pilot signals are utilized to approximate the desired signal and interference power, which yield the SINR measurements as well as the optimal digital weights. Since the selected analog beams based on the received power do not guarantee the hybrid beamforming achieving the maximization SINR, we therefore reserve additional analog beams as candidates during the beam tracking. The combination of analog beams with their digital weights achieving the maximum SINR consequently provides the optimal solution to the hybrid beamforming.

cs.IT↗

arXiv2018

Time-Domain Multi-Beam Selection and Its Performance Improvement for mmWave Systems

Multi-beam selection is one of the crucial technologies in hybrid beamforming systems for frequency-selective fading channels. Addressing the problem in the frequency domain facilitates the procedure of acquiring observations for analog beam selection. However, it is difficult to improve the quality of the contaminated observations at low SNR. To this end, this paper uses an idea that the significant observations are sparse in the time domain to further enhance the quality of signals as well as the beam selection performance. By exploiting properties of channel impulse responses and circular convolutions in the time domain, we can reduce the size of a Toeplitz matrix in deconvolution to generate periodic true values of coupling coefficients plus random noise signals. An arithmetic mean of these signals yields refined observations with minor noise effects and provides more accurate sparse multipath delay information. As a result, only the refined observations associated with the estimated multipath delay indices have to be taken into account for the analog beam selection problem.

cs.IT↗

arXiv2018

Hybrid Beamforming Based on Implicit Channel State Information for Millimeter Wave Links

Hybrid beamforming provides a promising solution to achieve high data rate transmission at millimeter waves. Implementing hybrid beamforming at a transceiver based on available channel state information is a common solution. However, many reference methods ignore the complexity of channel estimation for large antenna arrays or subsequent steps, such as the singular value decomposition of a channel matrix. To this end, we present a low-complexity scheme that exploits implicit channel knowledge to facilitate the design of hybrid beamforming for frequency-selective fading channels. The implicit channel knowledge can be interpreted as couplings between all possible pairs of analog beamforming vectors at the transmitter and receiver over the surrounding channel. Instead of calculating mutual information between large antenna arrays, we focus on small-size coupling matrices between beam patterns selected by using appropriate key parameters as performance indicators. This converts the complicated hybrid beamforming problem to a much simpler one: it amounts to collecting different sets of the large-power coupling coefficients to construct multiple alternatives for an effective channel matrix. Then, the set yielding the largest Frobenius norm (or the largest absolute value of the determinant) of the effective channel provides the solution to the hybrid beamforming problem. It turns out that the proposed method does not require information on MIMO channel and can be simply implemented by the received correlated pilot signals that are supposed to be used for channel estimation.

cs.IT↗

arXiv2018

Frequency-Selective Hybrid Beamforming Based on Implicit CSI for Millimeter Wave Systems

Hybrid beamforming is a promising concept to achieve high data rate transmission at millimeter waves. To implement it in a transceiver, many references optimally adapt to a high-dimensional multi-antenna channel but more or less ignore the complexity of the channel estimation. Realizing that received coupling coefficients of the channel and pairs of possible analog beamforming vectors can be used for analog beam selection, we further propose a low-complexity scheme that exploits the coupling coefficients to implement hybrid beamforming. Essentially, the coupling coefficients can be regarded as implicit channel state information (CSI), and the estimates of these coupling coefficients yield alternatives of effective channel matrices of much lower dimension. After calculating the Frobenius norm of these effective channel matrices, it turns out that the effective channel having the largest value of the Frobenius norm provides the solution to hybrid beamforming problem.

cs.IT↗